1. Field of the Invention
This invention relates generally to electronic communications and relates more particularly to a system and method for electronic communication management.
2. Description of the Background Art
In a typical organization, communications with customers and others may occur via a variety of different channels. In addition to traditional channels such as letters and telephone calls, customers may also communicate with an organization via electronic mail, facsimile, web-based forms, web-based chat, and wireless communication and voice. An organization will most likely incorporate these and any other newly developed communication channels to allow customers to communicate in a way they find most convenient.
Many of the communication channels mentioned above contain information that is unstructured in nature, usually expressed in natural language. Different customers may make identical requests each in a unique way, using different communication channels, different words, or both. Human agents are usually required to review each natural language communication to evaluate the customer's intent, and to determine what information or action would be responsive to that intent.
Agents typically must look to various sources to gather all of the information required to respond appropriately to a customer communication. The information may be retrieved from a variety of sources, such as legacy systems, databases, back office systems, and front office systems. Each of these sources may store data in a unique structure or format. An agent typically gathers and organizes the required information from one or more of these information sources and uses the information to compose an appropriate content-rich reply that is responsive to the customer's intent.
Utilizing people to respond to customer communications is often rather inefficient. In addition, an increase in the number of communications received by an organization typically requires an exponential increase in the number of people required to provide an acceptable level of customer service.
Several types of automatic systems exist for responding to customer communications. Rule-based systems, keyword-based systems, and statistical systems typically do not perform with the necessary accuracy to substantially automate business processes, such as responding to customer inquiries, and require a large investment in resources to keep them up-to-date. Many learning systems utilize a training set of data that is a poor representation of the system's world, which reduces the accuracy of the system and makes the process of updating the system very cumbersome.